The Peace and Well Being of Nations: An Analysis of Improved Quality
of Life and Enhanced Economic Performance Through
|Case Study: Mozambique has used Transcendental Meditation in the armed forces|
In Mozambique, President Chissano, whose country
was in the grip of a long-running civil war and economic chaos,
decided at the start of the 1990s to introduce the
Transcendental Meditation program to the armed forces and the
people of his nation. By the end of 1992, about 15,000 people
had learned the Transcendental Meditation technique and more
than 3,000 people were trained in the TM-Sidhi program including
Yogic Flying. After the introduction of the Transcendental
Meditation program news went around the world about the
transformation that the President had been able to effect in the
destiny of his nation. For example, a report in the 22 February
1993 New York Times said: "Mozambique has
unexpectedly emerged as a candidate for an African Success story
—We have a combination of peace and rain which has not been
seen in Mozambique for a quarter of a century'."
President Chissano attributes the cessation of
civil conflict in Mozambique and the ensuing development of his
country to the effect of the Transcendental Meditation program
—"First I started the practice of Transcendental
Meditation myself, then introduced the practice to my close
family, then to my cabinet of ministers, then to my government
officers, and then to the military. The result has been
political peace and balance in Nature in my country ... "
Mozambique has since experienced rapid economic revival with the country boosting GDP growth rate to 12.4% per year by 1997—the highest among all African nations, lowering inflation from 70% in 1994 to single digits by 1997, and reducing its massive net overseas debt from a peak in 1993 to a positive net asset in 1998. It has also successfully competed in the African market for manufacturing contracts, discovered the world's largest deposits of titanium, and enjoyed the most stable African currency values over an extended period. This has all happened while President Chissano had a policy of utilizing the Maharishi Effect to boost national stability and economic development.
Editor's Note: For more information, see also:
War and Peace in Mozambique - A Time Line - After serious critical study and analysis of the research on Invincible Defense Technology, the Joint Chiefs of Staff of the Armed Forces of Mozambique implemented Invincible Defense Technology in different military units of their Ground, Naval and Air Forces. To better understand the ramfications of their decision and the results of the research by Dr. Hatchard and Dr. Cavanaugh see this timeline summary of Mozambique's history since the 1960's to the end of the 1990's.
Mozambique's Prevention Wing Of The Military: End War, Improve The Economy - Article in Africa Economic Analysis, Dr. David R. Leffler and Mrs. Lee M. Leffler discuss the benefits gained from deployment of Invincible Defense Technology by the Mozambique Prevention Wing of the Military.
Invincible Defense--A New "Secret Weapon!" - Article published Canadian Centres for Teaching Peace. Retired Navy SEAL officer and scientists describe the deployment of, and underlying theory behind, the Prevention Wing of the Military deployed by Mozambique military to end their civil war.
In Somalia, peace negotiations began in January 1993 under the
auspices of the UN aimed at a transition to democracy and backed by the
presence of 28,000 UN peacekeeping troops failed to lead to progress.
The UN contingents were forced to withdraw and the country suffered
civil conflict and fragmentation throughout the 1990s. In late January
1993, there were peace talks between the Angolan government and UNITA
rebels in Addis Ababa with Portugal, Russia, and USA observing. A cease
fire was signed during September 1993. Despite UN supervised efforts to
implement the cease fire over a five-year period, by 1998 the country
had again descended into full civil war and economic chaos prevailed. In
contrast, the case studies of Cambodia and Mozambique are indicative of
broad social and economic progress along with cessation of conflict. The
authors are presently subjecting the limited available data to more
rigorous study. Previous research in USA provides supporting data and
|Case Study: The Maharishi Effect in Cambodia|
Maharishi Vedic University (MVU) Cambodia was
established in 1992 as a joint venture between the Royal
Cambodian Government, the Australian Aid to Cambodia Fund (AACF),
and MVU Holland to provide a Consciousness-Based Education to
rural youth who would not otherwise have access to higher
By 2004, MVU Cambodia has grown to occupy four
campuses with a total of over 1000 students. The unique feature
of the education system is the daily group practice of the
Transcendental Meditation technique and Yogic Flying. Cambodia
has a population of 10 million. The group at MVU is therefore
sufficiently large to pass the √1% Maharishi Effect
Following 1993, Cambodia has undergone a
remarkable transformation from a country with a civil war,
martial law, a military dictatorship, no freedom of expressions
or civil rights, a weak economy reliant on external assistance,
poor relations with neighbors, and a prevailing sense of fear,
intimidation and helplessness; to a democratic government with a
restored monarchy, freedom of expression and civil rights,
substantial foreign investment, greater self-sufficiency, much
improved relations with neighbors, now a member of the ASEAN
group of nations, and a much greater sense of confidence,
security and optimism. In Cambodia prior to 1993, there were few
reliable measures of social and economic factors available, but
recorded trends show reduced inflation (Fig. 1) and average real
GDP growth between 1994 and 2001 in excess of 5.5% p.a.
Cambodia Reduced Inflation (Annual change in
CPI mid year) 1990 - 2001
Since 1993, Cambodia has succeeded to a relatively significant extent in harmonizing conflicting groups and realizing a genuine base for social cooperative behavior, along with strong economic growth and relatively stable political institutions. Many MVU graduates now occupy leading roles in Cambodian society. In common with many political leaders, His Majesty King Norodom Sihanouk has publicly acknowledged that "MVU is playing an important role in human resource development and in restoration of peace and expansion of prosperity throughout the country." The resolution of conflict, the emergence of cooperative behavior and the resurgence of economic activity is really the hallmark of the Maharishi Effect.
Continuously between 1983 and 1989 inclusive and during specific other short periods a group of Yogic Flyers in Fairfield Iowa, USA at Maharishi University of Management was consistently larger than the square root of one per cent of the US population (approximately 1530 Yogic Flyers). Gelderloos et al (1988, 1990, 1996) used time series analysis and simultaneous transfer function models to analyze content of newspapers and public statements of US President Reagan. This showed that the size of the group of Yogic Flyers at Maharishi University of Management had a positive impact on US actions towards the USSR and vice versa, especially when the group size was large.
Stock market data can be interpreted as a measure of public
confidence and optimism. Orme- Johnson et al (1987) and
Cavanaugh et al (1984) used regression analysis and Box-Jenkins
time series analysis respectively and found a simultaneous rise in the
world's major stock markets during the assembly of 8000 Yogic Flyers
held at Maharishi University of Management, Iowa in December 1983 (p
< 0.00004). The rise had not occurred at that time of year for a
five-year previous period, nor did it occur in the control periods
before and after the assembly. The assembly accounted for 27% of the
variance in the World Index. Time series analysis that included 151 days
prior and 60 days after the assembly explicitly allowed for the effect
of long-term interest rates on international stock prices and found
similar highly significant effects (p < 0.000033). Prior
cyclical behavior of the World Stock Index did not predict any rise for
the experimental period.
Orme-Johnson and Gelderloos (1988) measured the impact of
participation in the Transcendental Meditation technique and Yogic
Flying in the USA on a quality of life index including 12 social
indicators. A reversal in the long term decline in US quality of life
occurred as large numbers of the USA population started the
Transcendental Meditation program and accelerated when the Maharishi
Effect threshold was exceeded. Cross-lagged correlations predicted
enhanced quality of life from the Transcendental Meditation technique
participation rate and showed this variable accounted for 44% of the
variance (p < 0.0001). Regression analysis yielded a similar
result (p < 0.0001). The economic portion of the index
reported GNP per capita as rising 2.3% in 1983 marking the end of the
recession, and a sharp decline in unemployment commencing in 1983.
In a series of studies covering 1979 to 1987 using Box-Jenkins time series analysis and multipleinput transfer function analysis, Cavanaugh et al. (1987-89) found sizable and highly statistically significant reductions in the monthly "Misery Index" (the sum of inflation and unemployment rates) in both USA and Canada during and following times when the coherence creating group of Yogic Flyers at Maharishi University of Management exceeded the square root of one per cent of the population threshold. The effect was larger when the group size was larger, and more significant in the USA, the country where the group was located, than in neighboring Canada. The studies statistically controlled for intensity of aggregate supply and demand shocks, influence of business cycle fluctuations, monetary growth, and growth of crude materials prices (food, energy, etc.). The group of Yogic Flyers accounted for 54% of the reduction in the US Misery Index from its peak in 1980 (p < 1x10-8). A significant unidirectional effect of the Yogic Flying group on the Misery Index was also found (p < 0.025) indicating that Yogic Flying participation was a causal factor.
GDP growth rate in USA: The key measure of US economic
health—annual Real GDP Growth Rate per capita enjoyed sustained growth
during the period of high US Maharishi Effect coherence between 1983 and
1989. The highest rate of annual growth of the series (5.9%) is recorded
in 1984 immediately following the assembly of 8,000 Yogic Flyers. All
three factors cited by the 1990 OECD US Economic Survey (OECD 1989-2002)
as underpinning the 1983 to 1989 growth of the US economy—reduced
unemployment, increase in stock prices, and reduced inflation—have
been reported by previous time series analysis to be significantly
related to the number of Yogic Flyers.
Given this, it is a reasonable hypothesis that the growth of the US
economy at that time was also related to the number of Yogic Flyers.
However Gross Domestic Product is composed of a huge a variety of
inputs. Due to the complexity of the mutual interactions and various
lags between sectors of the economy, GDP is not a good candidate for
analysis through the time series analysis process.
The detailed relationships in the quarterly figures at the various lags between the level of coherence and GDP will tend to get lost in the complexity and diversity of the input factors. Dillbeck and Rainforth (1996) confirm this view. Despite this, some support for this hypothesis is provided by the onset of sustained positive growth in US GDP in 1983 and by the large jump in GDP following the 8000 Assembly in 1984. The reduction in GDP growth rate in 1990 and the subsequent US involvement in international conflict as the size of the coherence group in Fairfield fell below the Maharishi Effect threshold after 1989 also supports this interpretation. This hypothesis would gain strength if there were other nations demonstrating similar effects.
The preceding case studies and previous research findings posed the authors an intriguing challenge—how to rigorously assess and quantify the impact of the Maharishi Effect on broadbased measures of national economic performance? The opportunity to assess this was provided by the two developed countries enjoying the world's highest levels of participation in the Transcendental Meditation program both of which passed the Maharishi Effect threshold during 1993.
Cumulative numbers of individuals instructed in the Transcendental
Meditation technique in New Zealand were obtained by the authors from
Maharishi Global Administration Through Natural Law (New Zealand). By
the end of 1993, there were 35,593 persons instructed in the Maharishi
Transcendental Meditation technique, 449 Yogic Flyers and 96 instructors
of the Transcendental Meditation program. The population of New Zealand
at the end of 1993 was 3,525,000 (New Zealand Government Census
Among the 46 countries covered by IMD data, the only other country to
have reached the target of one per cent instructed in the Maharishi
Transcendental Meditation program during the period covered by the IMD
rankings (1992 to 1998) was Norway. The baseline number instructed in
Transcendental Meditation in Norway at 1st January 1988 was recorded as
37,000 to 38,000 with the extended range accounted for by a small
recording error. Subsequently 2925 new individuals participated in the
Transcendental Meditation program before the end of 1993. By this time
there were over 400 Yogic Flyers some of whom practiced in groups
generating sufficient additional coherence to pass the Maharishi Effect
threshold. The population of Norway (OECD sources) was
4,287,000 in 1992.
New Zealand is a small, yet developed country. It is geographically
distant from the world, yet its very smallness means that it must depend
on exports and imports to maintain a well-mixed economic environment.
Traditionally the New Zealand economy has depended on exports of primary
products, particularly meat, wool, forestry, and dairy products, to pay
for needed imports. However, its economy gradually declined between 1950
and 1990, with attendant relative falls in standard of living as
compared to its major trading partners. Repeated interventions of
successive governments to correct the obvious imbalances in the
persistently sluggish economy had failed to produce a sustainable model
of economic success. But by 1994, it was apparent that a renewed
vibrancy had taken hold of the whole economy and the national mood.
Norway has an oil-rich economy, but despite the attendant wealth, the economy underperformed in the 1980's. Low domestic demand became linked with rising unemployment and a high rate of corporate failure, which affected bank solvency. By 1994, it was clear that domestic demand had unexpectedly began to increase ushering in an extended period of growth.
Measures of economic well-being of nations:
Michael Porter's analysis of "The Competitive Advantage of
Nations" (1990) has been adapted and augmented in econometric
approaches to measuring the economic well-being of nations. The IMD
Index contained in the IMD World Competitiveness Yearbook (IMD 1987-98)
is used in this study. It is a measure and database of the relative
national economic health of industrially developed nations that has
drawn upon Porter's ideas, but its broad base ensures that it is
independent of any particular theory. Madeleine Linard de Guertechin
defines the IMD Index in the 1997 World Competitiveness Yearbook as a
multidimensional approach "to capture in a single index the
capacity of a country's economic structure to promote growth".
The IMD Index is used to test the hypothesis that the economy of both
New Zealand and Norway showed a significant and broad-based improvement
in IMD scores relative to other developed nations at the time when they
surpassed the 1% threshold of individuals instructed in the
Transcendental Meditation program in 1993. The main conclusions of the
analysis are also checked against the conclusions of the independently
compiled OECD Economic Surveys.
Sources: The IMD Yearbook has been published
annually since 1987 by IMD, the International Institute for Management
Development in Switzerland. It contains a data base of economic and
social measures from industrially developed nations, which in 1996
comprised 224 data inputs for each of 46 nations. The 224 data points
data are combined through addition of z scores into 41 subscales, which
are in turn grouped into 8 categories3 and finally combined
into one overall competitiveness performance index (See Fig. 2) yielding
an annual ranking of the 46 countries.
Email communication with IMD indicated that the Index has been
compiled from 1992 to 1998 using a consistent methodology. This new
methodology was first used in 1996. At that time, the new method was
retrospectively applied to update the IMD Index for years 1992 - 1995.
OVERALL IMD SCORE
The data sources are made up of 35.5% that are per capita statistics
unrelated to country size such as interest rates or international credit
ratings, 10.7% absolute values that are positively affected by the size
of the country, 11.6% growth rates, 33.3% executive surveys, and 8.9%
background information. The IMD Yearbooks rank the 46 countries on each
set of the 224 raw data inputs (excluding the background statistics).
Each data set is then converted into z scores through the standard
Two thirds of the data sources involve hard or measured facts drawn
from a wide variety of international and national sources. Data sources
are referenced, missing values (2.9%) are handled efficiently, and data
issues of reliability and comparability are discussed in footnotes and
appendices. The remaining one third of the data series are derived from
up-to-date surveys of senior executives from the 46 countries. For
example in late 1995, a 72 question survey was sent out to 21,000
businessmen of whom 3,162 responded. This data was used in the 1996 IMD
Yearbook analysis. A similar procedure has been used in every other
The IMD Yearbooks report raw values for the data inputs, but all
compiled subscales and categories are quoted solely as rankings of
nations. The country with the best performance being ranked number 1 and
so on. To avoid this dilution of data, the authors obtained the series
of compiled z scores for the overall Index from IMD (See Table 1) and
used it in the main analysis. The effects of minor recorded data
irregularities are discussed and their correction estimated in the
The dependent variable is the IMD Index data (Table 1), which is a
repeated measure where each of 46 countries is observed at seven yearly
intervals in order to calculate a numerical value for overall
international competitiveness. Since the overall IMD Index score is
constructed from the addition of z scores, the mean of each year is
necessarily zero. Although the scores can in theory take any value, in
practice, no country moved outside limits of ±200. The standard
deviation of the IMD Index scores increased between 1992, when it was
sixty-three, to seventy-two in 1998.
Table 1: IMD Index of National Economic Well Being
Overall Scores 1992 - 1998* (compiled z scores)
New Zealand and Norway both surpassed the Maharishi Effect Threshold
(1% of the population for the Maharishi Transcendental Meditation
technique combined with √1% for groups of Yogic Flyers) during
1993. The target reporting date for the 1994 IMD Index data is mid 1993.
Therefore, in accord with previous practice, the independent variable
or Maharishi Effect Index was modeled as step function—zero for every
country except Norway and New Zealand in the years 1994, 1995, 1996,
1997, and 1998 when it was assigned the value one. This follows
established practice where the Maharishi Effect is described as a phase
transition phenomenon, which can be understood and analyzed in the same
way as transitions in physical systems (Hatchard et al. 1996).
Annual IMD index ratings for 46 countries formed a longitudinal panel
of data for the years 1992 through 1998. The cross-country panel data
were analyzed using dynamic panel regression methods.
A "fixed-effect" panel regression model for the IMD index
was formulated and then estimated using a procedure for cross-country
data proposed by Beck and Katz (1995). In this fixed-effect model (FEM),
the annual value of the IMD index for each country was modeled as a
linear function of three terms: (1) a country-specific regression
intercept (fixed effect) that provided an estimate of the mean of the
index for each country; (2) a regression coefficient designed to
estimate a hypothesized shift in the mean of the index for New Zealand
and Norway due to the Maharishi Effect; and (3) a random error or
disturbance term4. Each of the resulting set of regression
equations for the 46 countries had following simple form:
IMDit = βoi + β1 MEit + εit , i = 1, 2, ..., G; t
= 1, 2, ..., T (1)
In these equations IMDit is the IMD index for country i in year t, G is the number of countries in the sample (46) and T is the number of annual observations for each country (seven). The coefficient βoi is a regression intercept or constant term that differs across countries. The Maharishi Effect variable MEit is a "step-function" binary variable that takes the value 1 for the years 1994 through 1998 for New Zealand and Norway and is equal to 0 for all other countries and time periods. The parameter β1 is a regression coefficient that estimates the impact of the Maharishi Effect on the mean of the index for Norway and New Zealand. Finally, εit is a random error or regression disturbance term with mean zero.5
The parameters of the panel regression model were estimated using a
method suggested by Beck and Katz (1995, 1996). The Beck and Katz
approach allows for possibly differing variance of regression errors
across countries ("panel heteroskedasticity"), contemporaneous
correlation of errors across countries, and possible serial correlation
of residual errors. The latter three properties of the regression errors
are common in the analysis of cross-country data (Beck and Katz, 1995).
In the presence of any of the above three properties of the regression
errors, ordinary least squares (OLS) regression will not be optimal
(Beck and Katz, 1995, 1996).6 In this case the OLS estimates
of the regression parameters will be inefficient, although they are
unbiased and consistent (Beck and Katz, 1995; Greene, 2000, ch. 11).
More importantly, in this case the estimated standard errors for the
regression coefficients will be incorrect (biased and inconsistent) even
in large samples, thus invalidating standard tests of hypotheses (e.g., t-tests
and F-tests) (Greene, 2000, ch. 11-12; Beck and Katz, 1995,
1996). The method of Beck and Katz generates correct standard errors for
the purpose of hypothesis testing, so-called "panel corrected
standard errors" (PCSE).
The Beck-Katz Approach:
The first step in the Beck-Katz approach was to estimate the
fixedeffect model (1) using OLS regression. If diagnostic tests
indicated the presence of significant first-order serial correlation of
the regression residuals, the Prais-Winsten transformation of the data
was used to eliminate the observed serial correlation (Kmenta, 1986, p.
619). The equation was then re-estimated by OLS using the transformed
As recommended by Beck and Katz (1995) on the basis of Monte Carlo
simulation experiments, the Prais-Winsten transformation was based on a
common estimated serial correlation coefficient, rather than separate
coefficients for each country. The resulting regression estimates based
on the transformed data are equivalent to those produced by feasible
generalized least squares (FGLS) estimation of a regression model with a
first-order autoregressive (AR(1)) model for the errors (Greene, 2000,
An advantage of the Prais-Winsten approach is that, in contrast to the Cochran-Orcutt transformation, it does not involve discarding the first data observation for each country, leading to increased efficiency of the resulting OLS estimates (Greene, 2000, pp. 546 547). Since only 7 annual observations were available for the IMD index for the 46 countries, retaining the first observation was an important consideration. This issue was particularly salient for tests of the Maharishi Effect because only two annual values of the index were available for the baseline period prior to the predicted onset of the Maharishi Effect for New Zealand and Norway in 1993 (as reflected in the IMD index data for 1994).
After removing the serial correlation of residuals in the first step
of the Beck-Katz procedure, the OLS estimates of the regression slope
parameters for the fixed-effect model (1) will be unbiased and
consistent. However the estimated standard errors for the parameter
estimates will still be incorrect (biased and inconsistent) if the
regression errors display either differing error variance across
countries, cross-country correlation of the errors, or both. Because the
OLS parameter estimates will be correct after any serial correlation of
the errors has been removed, Beck and Katz propose basing hypothesis
tests on the OLS parameter estimates of the transformed data from step
one using corrected standard errors (PCSEs).7
Beck and Katz (1996) prove that the resulting PCSEs are consistent. Simulation experiments (Beck and Katz, 1995, 1996) indicate that in typical cross-country studies the corrected standard errors will be accurate even in the presence of contemporaneously correlated (panel heteroskedastic) errors. Their simulations also suggest that the efficiency loss of using the OLS parameter estimates "would not be large in practical research situations" (Beck and Katz, 1996, p. 5).
In summary, the specification of the independent Maharishi Effect
variable as a step function enables the panel regression model to
provide an "impact assessment" of the Maharishi Effect
intervention on the mean level of the IMD Index for Norway and New
Zealand allowing for a common autoregressive error structure as well as
a contemporaneous correlation of errors and differing error variance
across countries. With this approach, the analysis will answer the
question 'Is a significant increase in competitiveness score predicted
by the increase in coherence, taking into account the time-dependent,
dynamic structure of the IMD panel of scores?'
RESULTS OF PRIMARY ANALYSIS
The primary analysis employs panel regression analysis to determine
the significance of the increases in the level of the IMD Index for the
1994-1998 as compared with the 1992-93 baseline period. The dependent
variable for the analysis was the annual value of the IMD index
(compiled z scores) for the full set of 46 countries ranked by the IMD
over the years 1992-1998. The sample included seven annual observations
for each of the 46 countries, giving a total of 322 observations. There
were no missing data values. The regression results for the primary
panel data analysis of the IMD index are summarized in Tables 2 and 3.
Results were calculated using LIMDEP 7.0 and EViews 3.1 for Windows.
Table 2 displays the initial ordinary least squares (OLS) regression
parameter estimates for the fixed-effects model (FEM) described in
equation (1). As hypothesized, the sign of the estimated impact of the
Maharishi Effect on the IMD index for New Zealand and Norway was
positive. The estimate of the Maharishi Effect parameter β1
indicated an upward shift of 36.545 in the mean level of the IMD index
for the two countries, on average, for the years 1994 through the end of
the sample in 1998 (p = 3.3 x 10-5, two tailed
As shown in Table 2, the overall F statistic for the regression was statistically significant, indicating that the parameter estimates for all explanatory variables in the regression take together, including the estimated regression intercepts for each country, were significantly different from zero. In order to conserve space the estimated country-specific intercepts are not shown in Tables 2 and 3 (Complete regression results are available upon request from the first author). The reported Rsquared value for the regression implies that the estimated model accounted for 96.1 percent of the variation in the IMD index.
Diagnostic tests reported in Table 2 indicate violation of important
assumptions underlying the OLS regression analysis. First, the Lagrange
multiplier (LM) test for first-order serial correlation of the
regression residuals was statistically significant, with an estimated
serial correlation coefficient of 0.388. The latter test is the Breusch-Godfrey
test for first-order serial correlation (Godfrey, 1988; Greene, 2000, p.
541). Second, the LM test for differing variances for the regression
errors across countries was highly significant (Greene, 2000, pp.
594-596), indicating violation of the OLS assumption of constant
variance of the regression disturbances. Third, inspection of the
(contemporaneous) correlation matrix of the regression residuals
indicated substantial crosscountry correlation of the errors, with a
majority of the correlations varying from 0.5 to 0.9 in absolute value.
As in Beck and Katz (1995, 1996) no formal test was employed because the
crosscountry correlations are imprecisely estimated.8
As described above, in the presence of any of these three violations
of the standard OLS error assumptions, the standard errors for the
estimated parameters will be incorrect (biased and inconsistent), thus
invalidating hypothesis tests for the estimated parameters.
Consequently, in order to perform valid hypothesis tests the Beck-Katz
procedure (Beck and Katz, 1995; Greene, 2000, ch. 15) was used to
correct the OLS standard errors reported in Table 2.
Panel Regression Analysis of IMD Index, 1992-1998
Ordinary Least Squares (OLS) Regression Estimates of Fixed Effects Model
Dependent Variable: IMD Index (Compiled Z Scores)†
|Variable||Coefficient||Standard Error||T-Ratio||P Value|
|Maharishi Effect||36.545||8.655||4.223||3.3 x 10--5|
|Number of observations 322||Degrees of freedom 275|
|F-statistic F(46, 275) 145.48 (p = 0.000)||R-squared 0.961|
|S.E. of regression 14.629||R-bar-squared 0.954|
|Sum of squared residuals 58852.80||S.D. of dependent variable 68.153|
|Lag-one serial correlation 0.388||Mean of dependent variable -2.07 x 10-12|
|Durbin-Watson statistic 1.119||Akaike information criterion 2684.85|
|LM test for serial correlation:2(1) = 70.574 (p = 0.000)||LM test for panel heteroscedasticity:2(45) = 146.7808 (p = 0.000)|
|Test of pooled regression vs. fixed effects: F(45, 275) = 144.913 (p = 0.000)||Jarque-Bera test for normality:2(2) = 12.845 (p = 0.002)|
† The dependent variable was the net improvement in year-to-year net subscale ranks (transformed to z-scores) for the IMD Index. The data consisted of 4 annual observations (T = 4) on each of 36 countries (G = 36) with complete data, yielding a total sample of 144 observations.
Correction for Violations of the OLS Error Assumptions:
In the Beck-Katz procedure, all regression variables for the
fixed-effects model were first transformed to eliminate the serial
correlation of residuals and then the model was re-estimated by OLS. The
resulting estimates are shown in the top panel of Table 3. After
adjusting parameter estimates for residual serial correlation,
panel-corrected standard errors were calculated to provide estimated
standard errors that are robust to panel heteroskedasticity and
contemporaneous correlation of the residuals. The calculation of the
PCSEs provides corrected estimates of the OLS standard errors, but does
not alter the OLS parameter estimates that have been adjusted for serial
correlation. Nor does the adjustment process for the standard errors
change the summary and diagnostic statistics for the regression. The
resulting corrected standard errors (PCSEs) are reported in the lower
panel of Table 3.
Corrected Panel Regression Analysis of IMD Index, 1992-1998
OLS Regression Estimates Corrected for Serial Correlation with Standard Errors Robust to Panel Heteroskedasticity, and Cross-Country Correlation of Residuals
Dependent Variable: IMD Index (Compiled Z Scores)†
OLS Estimates Corrected for Residual Serial Correlation:
|Variable||Coefficient||Standard Error||T-Ratio||P Value|
OLS Estimates Corrected for Serial Correlation with Standard Errors Robust to Panel Heteroskedasticity and Cross-Country Residual Correlation:
Panel Corrected Standard Error
|Maharishi Effect||43.023||4.961||8.672||2.9 x 10-15|
|Number of observations 322||Degrees of freedom 275|
|F-statistic F(46, 275) ) 62.82 (p = 0.000)||R-squared 0.913|
|S.E. of regression 14.469||R-bar-squared 0.899|
|Sum of squared residuals 57572.16||S.D. of dependent variable 45.430|
|Lag-one serial correlation -0.026||Mean of dependent variable -1.43 x 10-12|
|Durbin-Watson statistic 2.052||Akaike information criterion 2677.76|
|LM test for serial correlation: 2(1) = 0.244 (p = 0.622)||Jarque-Bera test for normality: 2(2) = 7.986 (p = 0.018)|
|Test of pooled regression vs. fixed effects: F(46, 275) = 61.245 (p = 0.000)||LM test for panel heteroscedasticity:2(45) = 84.702 (p = 0.0003)|
|Ramsey's RESET test for omitted variables: F(3, 272) = 1.678 (p = 0.172)|
† Prior to OLS estimation, the dependent and independent variables were transformed using the Prais-Winsten transformation to remove first-order serial correlation of residuals (r1 = 0.388). To conserve space, the 46 estimated country-specific intercepts (fixed effects) are not shown. These intercepts were jointly significant. Complete regression results are available from the authors.
In the first step of the Beck-Katz procedure, the Prais-Winsten
transformation was separately applied to all variables for each country.
As recommended by Beck and Katz (1995), the transformation was based on
single, common, estimated serial correlation coefficient for all
countries, rather than separate coefficients for each country. The
common estimated serial correlation coefficient was 0.388 (Table 2). The
OLS parameter estimates that have been corrected for serial correlation
are equivalent to those from a regression model with first-order
autoregressive (AR(1)) errors that was estimated using feasible
generalized least squares.
After adjustment for serial correlation, the estimated Maharishi
Effect parameter indicated a significant upward shift in the mean of the
IMD index for Norway and New Zealand of 43.023 units (refer to top panel
of Table 3). The latter parameter estimate is unbiased and consistent
(Beck and Katz, 1995; Greene, 2000, ch. 11), but its estimated standard
error remains incorrect (biased and inconsistent) because the LM test
for panel heteroskedasticity in (Table 3) indicates the presence of
significantly different error variances across countries. Substantial
remaining crosscountry correlation of residuals was also found, which
also implies biased and inconsistent OLS standard errors.
The non-significance of the LM test for serial correlation (Table 3)
indicates that the Prais-Winsten transformation was successful in
removing the serial correlation of the regression residuals. The
Rsquared value for the regression was 0.913, indicating that the
regression accounted for 91.3 percent of the variation in the index.
Note that because the dependent variables have been transformed, this
R-squared value cannot be validly compared to that reported in Table 2.
The overall F-statistic was significant, as was the F-test
for the joint significance of the country-specific intercept terms for
the fixed effect model. Ramsey's RESET test (Godfrey, 1988; Kennedy,
1998, p. 98, 80) was not significant, indicating no evidence of omitted
explanatory variables or incorrect functional form of the regression
The lower panel of Table 3 reports the panel-corrected standard error
for the Maharishi Effect parameter. The PCSE for the Maharishi Effect
parameter reported in Table 3 is robust to both panel heteroskedasticity
and cross-country correlation of the regression disturbances (Beck and
The PCSE for the estimated Maharishi Effect parameter is
substantially smaller than that resulting from adjustment for serial
correlation alone (top panel of Table 3). This reduction in the standard
error results in a larger t-ratio for the estimated Maharishi
Effect parameter t(275) = 8.672, with p-value 2.9 x 10-15.
In addition to being statistically significant, the latter estimate was
also substantively important, representing 61.7 percent of the standard
deviation of the untransformed IMD index (43.023/68.153).
Table 3 reports several diagnostic tests of model adequacy. These
tests include an F-test of the "pooled regression"
model versus the fixed-effects model (Baltagi, 1995, p. 12; Greene,
2000, p. 562). The pooled regression model includes only a single common
intercept term, as contrasted with the FEM reported in Table 3, which
incorporates a separate intercept for each country. The F-test
rejects the null hypothesis that the country-specific intercepts are
jointly equal to zero, thus indicating that the pooled regression model
is not a valid restriction on the fixed-effects model.
A further issue regarding the interpretation of the regression
results in Tables 2 and 3 is the apparent non-normality of the
regression residuals. The Jarque-Bera test (1987) reported in both
tables was statistically significant, indicating rejection of the null
hypothesis that the regression residuals were drawn from a normal
distribution. However, the distribution of residuals was not grossly
non-normal. The histogram was bell-shaped, displaying mild negative
skewness (-0.280) and positive kurtosis (3.531), as compared to the
expected values of 0.0 and 3.0, respectively, for a normal (Gaussian)
Even in the presence of grossly non-normal errors, under fairly
general conditions the OLS regression parameters remain correct
(unbiased and consistent) and are approximately (asymptotically)
normally distributed in large samples (Fomby et al., 1984, p. 62-63).
This result also extends to the case in which the errors are
heteroskedastic and serially correlated (Greene, 2000, pp. 458-460). The
usual hypothesis testing procedures, such as t-tests and F-tests,
also remain asymptotically valid for large samples (Fomby et al., 1984,
p. 62-63). The significance of the test for normality in this case
appears to be due to the very large sample size (322 observations) since
the deviation from normality appears to be slight. Thus it appears
unlikely that the observed mild departure from normality of residuals
has any important implication for the interpretation of the empirical
results shown in Table 3.
In sum, the estimated impact of the Maharishi Effect on the mean level of the IMD index for New Zealand and Norway remained substantial in size and highly significant after correction for serially correlated errors, differing variance of the regression residuals across countries (panel heteroskedasticity), and cross-country correlation of the errors. This significant estimated upward shift in the mean IMD index lends support to the hypothesis of a sudden improvement in the economies of New Zealand and Norway triggered in 1993 when both countries reached the predicted critical threshold of one percent of the national population instructed in the TM technique.
To further assess the appropriateness of the Maharishi Effect phase
transition model and to more fully understand the character of the
economic and social changes that occurred in New Zealand and Norway with
the onset of the Maharishi Effect, the following three subsections
(Correction of Data Irregularities, Subsidiary Analysis, and Discussion)
examine the data sources and individual country performances in detail.
Also the nature of the improved economic and social performance in New
Zealand and Norway is compared to those of other countries. The latter
discussion shows that for countries other than New Zealand and Norway,
most cases of sharp upward movement in the IMD Index are the result of
short-term volatility. In contrast, the improved performance of New
Zealand and Norway on the IMD Index in 1994 is broad-based and then
largely sustained over the subsequent five-year period. From this point
of view, the large effect size and the high statistical significance
obtained in the panel regression analysis are not surprising. Some
alternative statistical approaches were used in preliminary analysis of
the panel data, all of which were highly statistically significant
indicating that the significant results reported in Tables 2-4 are quite
robust to the method of analysis employed. To substantiate these
results, the Discussion section will investigate the logical basis for a
causal inference from the data.
CORRECTION OF DATA IRREGULARITIES
The statistical results need to be discussed in the light of any
identified irregularities in the input data series that contribute to
the IMD Index.
Size: The IMD Index is calculated to favor countries
with a higher population since size is considered an aid to competitive
advantage. Twenty four (10.7%) of the 224 IMD data sources are directly
related to the size of the country. Some examples include Gross Domestic
Measures of Total Investment, Number of Computers in Use, Number of Fortune 500 Companies, Size of Banks, etc. In effect, a larger country has a greater potential to be ranked higher. This adds significance to the relatively high IMD Index score of New Zealand and Norway, which were ranked 11th and 6th by score in 1996, but only 43rd and 41st on population size.
The IMD scores can be recalculated by excluding absolute values (the excluded data is still represented in the resulting scale since IMD uses both absolute values and per capita values). An adjusted Index can be calculated by subtracting the z scores for the 24 affected data points from the overall IMD Index scores reported in Table 1.
Timing: The target timing of reported data lags by
one year behind the publication date of the IMD Yearbook, which comes
out in May of the quoted year. Thus the average reporting date for 1994
rankings is mid 1993. Data for New Zealand lagged an average of 0.3
years behind the overall target date. This lag was not evenly
distributed. By inspection it was determined that lags could potentially
influence outcomes for 12 out of the 41 subscales. Norway data timing
only lagged 0.13 years behind the target date and had very little impact
on overall scores.
For six subscales, the change in the New Zealand subscale ranks for
the following year 1994/1995 more accurately gauged the actual
improvement in the 1993/94 time frame. These were Economic Sectors,
Export of Goods and Services, Imports of Goods and Services, Patents,
Energy Self- Sufficiency, and Educational Structures. In these cases,
the time lags meant that the Four of these subscales showed larger
improvements for 1994/95 than for 1993/94, one remained unchanged, and
one showed that a fall for 1993/94 had become a rise in 1994/95.
For the National Debt subscale, two out of four New Zealand figures
were three years out of date. OECD data shows that New Zealand reduced
its net national debt during that three-year period. This would have
improved New Zealand's ranking by 6 ranks. The 1993/94 subscale rank
remained unchanged on the IMD Index. It should have been recorded as a
For the Government Expenditure subscale, New Zealand data for levels
of government employment was seven years out of date. OECD data shows
that overall government employment in central administration and defense
fell by 6% between 1989 and 1993. Therefore the ranking on the
Government Expenditures subscale should have been higher than it
actually was, but the size of the annual change for 1993/94 was positive
and therefore was not corrected.
For the Environment subscale, figures for all countries lagged three
years behind the target date therefore this scale is not useful for
assessing improvements in 1993/1994. The Productivity subscale has five
data inputs. For New Zealand, one was missing, one was up to date, one
was a 1990/95 trend for overall productivity, one was two years out of
date, and crucially important, agricultural productivity was five years
out of date. OECD data reports that the New Zealand economy grew 0.5% in
1990, shrank 1.8% in 1991, resumed a slow upward trend in 1992, and then
grew more rapidly in 1993 to attain an annual value of 5.5% by 1994, the
largest among OECD countries. Therefore, although the Productivity
subscale showed an improvement in rank, the size of the improvement
(only one place) is too small.
For the R & D Resources subscale, four of the six New Zealand
data inputs are three years out of date, one is two years out of date,
and one is up to date. New Zealand's rank on this subscale declined in
the 1994 IMD Index and then resumed an upward trend in the 1994, 1995,
and 1996 IMD publications. Therefore, it is assumed that the positive
change recorded in the 1995/1996 IMD publications more accurately
reflect the conditions prevalent in 1993.
Data irregularities had an impact on performance in only one subscale
of the Norwegian data. Two out of three figures for Capital Formation
were one year out of date, while the fourth factor was a four-year
growth rate. This subscale declined between 1993/94, but increased
strongly between 1994/95, which more accurately reflects the Capital
Formation in 1993/94.
Trends: 26 data inputs (11.6%) are trends. These
trends are variously reported over 3 to 5 years as average annual growth
percentage rates, annual compound percentage growth rates, or geometric
means. The sharpness of the improvements in the New Zealand economy in
1993 evident in OECD Surveys (1989-2002) demonstrates that data from
trends used in the IMD Index will greatly underestimate the rapid
improvement in the economy and expansion in business confidence, which
occurred during 1993. Thus the impact of trends used in the IMD Index
will mean that the regression analysis reported in the previous section
underestimates the significance of improvements in the New Zealand
economy. A similar, though less marked effect, is evident in the
oil-based Norwegian economy, which experienced an unexpected surge in
domestic growth beginning in 1993 at 2%, and doubling in 1994 to a
Correction of IMD scores for data irregularities: The detailed
consideration of subscales shows that the analysis would be more
accurate if timing could be adjusted, and more so if the effect of
trends and size were also partialed out of the analysis. Whilst the time
involved in such data collection and adjustment is prohibitive for the
single researcher (the analyzed panel data is derived from 72,128 single
data inputs), it has been possible to estimate the effect that the
adjustment of timing and size would have on the overall rank of New
Zealand and Norway for 1993 and 1994. This involves an approximation—a
proportional approach to adjust the 41 subscales recorded as ranked data
only in the 1996 yearbook. Each subscale accounts for a specific known
proportion of the overall IMD index according to how many source data
points feed into the calculation of the overall Index. If 1993/94 New
Zealand data is on average one year out of date on a particular subscale
compared to data from other nations in the same category, the 1994/95
subscale ranking of New Zealand can be used to proportionally adjust the
1993/94 rank to more accurately reflect the 1993/94 change.
This is a relatively simple, if time consuming, procedure. It is also
the most conservative method of adjusting the IMD Index for timing that
can be adopted. No adjustments for the effect of growth rates averaged
over time were used. Our protocol underestimated the score and rank of
New Zealand and Norway in 1994 as compared to the effect of completely
recalculating the IMD Index.
After this proportional adjustment, the z scores of the 24
'size-related' categories were subtracted from the IMD Index. On the new
scale, which more accurately reflects the 'economic vibrancy' of
countries, New Zealand rose from 38.75 in 1993 to 78.05 in 1994. A rise
of 39.3 units (compared to 23.89 on the unadjusted scale). Norway rose
from 27.69 in 1993 to 55.42 in 1994. A rise of 27.73 units (compared to
26.47 on the unadjusted scale). Since it was not feasible to adjust the
data for the remaining 44 countries, the corrected scale must be
considered preliminary. However, the relatively high proportion of
timing irregularities in the New Zealand analysis justifies the utility
of this partial approach to data correction. The more so since the
majority of other data irregularities are clustered among a few
countries such as Russia, which are near the bottom of the IMD Index,
well away from New Zealand and Norway. It is evident that the correction
of the IMD Index for New Zealand and Norway would have a large positive
impact on both the statistical significance of the size of the change
between 1993/94 and on the overall rank of both countries in 1994 (New
Zealand is 5th overall and Norway 10th on the resulting Economic
Vibrancy Scale10 ).
Breadth of Improvement on Index Subscales: The IMD
reports ranks for each country for 1992-1996 on the 41 subscales that
contribute to the overall IMD Index. Subsidiary analysis of these ranks
was undertaken to test whether the improvement of factors contributing
to the rise in IMD scores was broad-based.
For each country and each year, the number of subscales that
increased or fell in rank were recorded as a positive or negative
integers; by summing these two figures an overall performance of
'integer change in rank' for subscales is obtained for each country for
each pair of years. For 1993/4, New Zealand improved its rank on 26
subscales, remained unchanged on 11 and fell back on 4 subscales. Norway
improved its rank on 28 subscales, remained unchanged on 7, and fell
back on 5. Thus for 1993/94, New Zealand's score was 26 - 4 = +22 and
Norway's score was 28 - 5 = +23. For each of the 36 countries with
complete subscale data for all years of the sample, the net number of
subscale ranks showing improvement from the previous year was calculated
for each country for 1993-1996. The net improvement in subscale ranks
was calculated as the number of increased ranks minus decreased ranks.
The resulting integer net-improvement totals were then converted to z
scores for statistical analysis. The sample included four annual
observations for each of 36 countries, yielding a total of 144
observations. Adjustments of timing for New Zealand and Norway were then
incorporated into the subsidiary analysis of subscales using the
information reported previously. Now New Zealand shows a net gain in
rank of +27 out of 39 available subscales and Norway +25 out of 40
Figure 4 plots all the rank sums for all countries for all years 1992
to 1996 with the New Zealand and Norway figures corrected for timing
Figure 3: Annual Change in 41 Subscale Ranks—positive minus negative change (1992/96)
Analysis of breadth of improvement on IMD Index subscales: Panel
regression analysis was used to test the hypothesis that the onset of
the Maharishi Effect in 1993 (as reflected in the 1994 IMD index data)
resulted in a significant average net improvement in subscale ranks for
New Zealand and Norway relative to other countries in the sample. This
subsidiary analysis, thus, investigated the hypothesis that the latter
two countries showed an improvement in the IMD index from 1993 to 1994
that was significantly more broad-based than that experienced by the
other 34 countries. To estimate the impact of the Maharishi Effect, a
binary dummy variable was included as an explanatory variable that took
the value 1 for the observation corresponding to the change in ranks
from 1993-1994 for New Zealand and Norway and was otherwise equal to 0.
The dependent variable in this regression is a year-to-year change
In the initial step of the analysis, a fixed-effect model for the rank-improvement data was estimated using ordinary least squares regression (not shown). The F-test for the pooled regression model versus the FEM indicated that the country-specific intercepts, taken together, were not statistically significant from zero (Table 4). Since the pooled regression model could not be rejected as a restriction on the FEM, the country-specific intercepts were dropped from the regression equation and replaced by a common intercept. The resulting pooled OLS regression estimates are summarized in the top panel of Table 4.
Panel Regression Analysis: Breadth of Improvement in Subscale Ranks, 1993-1996
OLS Pooled Regression Estimates with Standard Errors Robust to Panel Heteroskedasticity and Cross-Country Residual Correlation
Dependent Variable: Year-to-Year Net Improvement in Index Subscale Ranks†
|Variable||Coefficient||Standard Error||T-Ratio||P Value|
|Maharishi Effect||27.592||6.437||4.287||3.3 x 10-5|
OLS Estimates with Standard Errors Robust for Panel Heteroskedasticity and Cross-Country Residual Correlation:
Panel Corrected Standard Error
|Maharishi Effect||27.592||5.106||5.404||6.5 x 10-8|
|Number of observations 144||Degrees of freedom 142|
|F-statistic F(1, 142) 18.376 (p = 0.0003)||R-squared 0.115|
|S.E. of regression 9.039||R-bar-squared 0.108|
|Sum of squared residuals 11602.31||S.D. of dependent variable 9.573|
|Lag-one serial correlation -0.132||Mean of dependent variable -1.208|
|Durbin-Watson statistic 2.264||Akaike information criterion 1044.69|
|LM test for serial correlation: 2(1) = 2.603 (p = 0.107)||LM test for panel heteroscedasticity: 2(35) = 41.987 (p = 0.194)|
|Test of pooled regression vs. fixed effects: F(35, 107) = 0.672 (p = 0.910)||Jarque-Bera test for normality:2(2) = 0.569 (p = 0.752)|
† The data consisted of 7 annual observations on each of 46 countries, for a total sample size of 322. To conserve space, the 46 estimated country-specific intercepts (fixed effects) are not shown. These intercepts were jointly statistically significant. Complete regression results are available from the authors.
The overall F-statistic indicated that the regression was
significant. The R-squared value of 0.115 indicates that the regression
explained 11.5 percent of the variability of the dependent variable. The
R-squared values for this regression cannot be meaningfully compared to
those for the regressions reported in Tables 2-3 because the dependent
variables are different. As is common with data expressed as change
scores or first-differences, the proportion of variance explained is
relatively small, indicating the presence of a great deal of
"noise" in the rank-improvement data. It is well known that
transforming a variable to first differences (change scores) amplifies
the proportion of its variance that is due to random noise, leading to
reduced R-square values.
Despite the small proportion of variance accounted for by the model, the magnitude of the estimated Maharishi Effect parameter was both statistically significant (p = 3.3 x 10-5) and substantial in magnitude. The parameter estimate is nearly three (2.88) times the size of the inherent variability of the dependent variable, as measured by the latter's standard deviation (Table 4). By the standards of social science, this is a very large effect.
Except for the presence of substantial contemporaneous correlation of
residuals across countries, diagnostic tests indicated that the other
statistical assumptions of the regression analysis were satisfied.11
The test for first-order serial correlation of the residuals indicated
that the observed serial correlation coefficient (-0.132) was not
statistically different from zero. Re-estimation of the model using
transformed data based on the Prais-Winsten transformation indicated
that the results reported in Table 4 were not substantially affected by
the presence of this (non-significant) serial correlation of residuals.
After adjustment for first-order serial correlation, the estimated
Maharishi Effect parameter was slightly larger, 28.694, and significant
(t(142) = 4.515, p = 1.3 x 10-5).12 In
other diagnostic tests, the LM test for heteroskedasticity of the
regression errors across countries was not significant, and the null
hypothesis of normally distributed errors could not be rejected (Table
To correct for the presence of cross-country correlation of the
errors, panel-corrected standard errors (PCSEs) were calculated. The
lower panel of Table 4 shows that the resulting PCSEs are smaller than
the OLS standard errors, yielding a corrected t-statistic for the
Maharishi Effect parameter of t = 5.504 (p = 6.5 x 10-8
). Thus these results lend support to the hypothesis that New Zealand
and Norway, on average, displayed an improvement in the IMD index from
1993-1994 that was substantially and significantly more broad-based than
that experienced by the remaining 34 countries in the sample.
The statistical analysis has already measured the significance of the
rises in Norway and New Zealand relative to all individual changes
including any other large rises. To assess further whether this change
was unique, the annual change for each year and each country was
expressed as a percentage of the standard deviation for the overall
scores in that year. New Zealand rose by 35% in 93/94 and Norway by 39%.
All other annual changes in scores were inspected; those above 25% are
discussed on a case-by-case basis as follows.
The IMD scores show some volatility13, but most of the
larger rises tend to be relatively short lived. This was true of
Argentina, Chile, Korea, Taiwan, Philippines, United Kingdom, Russia,
Poland, Spain, and Luxembourg. None of the above fitted the step
function model used to assess the significance of rises in New Zealand
and Norway. Only Canada (24% and 25% between 94/96), Ireland (27% in
96/97), USA (34% in 96/97), Hungary (36% in 97/98), China (30% in 95/96
and 32% in 97/98), and Finland (43% in 96/97) have had sustained annual
rises of more than 25% of the standard deviation of IMD scores. The
influence of the Maharishi Effect on Canada and the USA created by the
coherence creating group in Iowa has already been discussed. In fact,
many Canadians participate in the coherence creating group in Fairfield,
Iowa. Similarly, there is a UK coherence creating group in Merseyside
with many Irish participants. The authors cannot assess the impact of
such groups on their IMD performance. China and Hungary are rising in
economic performance from a very low relative base line and are
therefore not strictly comparable with New Zealand and Norway.
Finland does have a comparable economy but it does not have a
coherence creating group. Its IMD score improved 43% of the SD between
1996 and 1997, larger than the 1993/94 changes in Norway and New
Zealand. OECD Surveys throw light on the nature of the economic
resurgence in Finland. Prior to their collapse in 1990, Finland had a
strong economic relationship with the countries of the former Soviet
Union. From mid 1990 up to 1993, Finland's real GDP fell by almost 15%
and unemployment rose from 3.5% to 19%. The terms of trade deteriorated.
There was a financial crisis resulting in the devaluation of the
currency. Following this, the 1995 OECD Finland Economic Survey
concluded that the strong recovery of exports to former Comecon
countries was striking, with Finnish sales to Central and Eastern Europe
currently returning to levels that prevailed just before the collapse of
trade with this region in 1990/91.
During this recovery, exports to the EU remained largely stagnant and
unemployment was still running at 17% in 1996. In 1997, the OECD Survey
reported that Finland had fully recovered the enormous loss in output
that it sustained after the collapse of the Soviet Union. Therefore the
large rise in IMD Competitiveness ratings for Finland between 1996 and
1997 was actually a recovery from the massive economic shock that the
country sustained after the collapse of the Soviet Union.
Nor did Finland enjoy the balanced nature of the recovery in New
Zealand and Norway where unemployment fell as the economy gained speed14,
as confirmed by OECD Surveys.
Analysis of Causality: The improvement in the
competitiveness scores of Norway and New Zealand is highly statistically
significant, but it is important to discuss the reasons why they lend
support to a causal interpretation. The analysis has established a
strong correlation between events; on their own, correlation and
simultaneity of events only strengthen causality arguments, but do not
prove causality. Granger (1969) suggests that the temporal sequence of
events is crucial to establishing causality. In essence, if X precedes
Y, then X is a good candidate for a causal factor, but Y is not.
Moreover, because economic systems involve a complexity of mutually
interacting variables, if X is clearly exogenous to the existing
economic system then the argument for causality is strengthened (Zellner
1988). Hendry and Richard (1982) agree and place emphasis the need for a
satisfactory explanatory model. More than this, the examination of other
potential causal factors is essential. With these factors in mind, we
can discuss the arguments for causality.
Timing: Within the limits imposed by annual data,
the statistical analysis shows that there was a significant improvement
in a broad measure of the economic health of Norway and New Zealand at
the time predicted by theory, when the Maharishi Effect threshold was
surpassed. This shows a correlation, which lends support to a causal
hypothesis. The subsidiary analysis, which makes the timing of the data
inputs more exact, strengthens this correlation considerably.
Examination of all other relatively large individual movements in
national IMD Index scores, has shown that most of these were examples of
volatility or due to other causes.
Economic forecasts: OECD forecasts did not predict correctly the speed, timing, and depth of the improvements in the Norwegian and New Zealand economies. In retrospect, in 1998 the OECD reached the conclusion that 80% of the massive New Zealand government debt repayment achieved between 1994 and 1998 was not predicted by prior cyclical trends (see Cost Benefit Analysis). Moreover, most influential New Zealand economic commentators did not see any prospect of significant short-term economic recovery even as late as 1992. For example, in a landmark study of the New Zealand economy, Michael Porter and Graham Crocombe wrote in 1991:
This broad-based change came about not slowly through changes in attitudes,
institutions, policies, and strategies as Porter and Crocombe
suggest, but rapidly pointing to a novel cause such as the Maharishi
Effect. Nor did the World Bank anticipate the rapid recovery in
Mozambique, which we have discussed. These results are suggestive of the
capacity of Maharishi Effect theory to predict economic improvements
that were not anticipated by traditional economic theory.
Other economies: Case studies of the Maharishi Effect are reported for Cambodia, Mozambique, and USA, which record very similar broad-based improvements. These case studies strengthen causality arguments since they imply that the Maharishi Effect theory is robust, repeatable, and portable; especially since these three economies are radically different from one another. Cambodia and Mozambique are formerly the poorest nations in the world, and USA is arguably the richest. The authors have published elsewhere (Hatchard et al 1996, 2000) another case study of improved economy and quality of life in Merseyside, which is an industrial metropolitan area.
Replication: Repeated demonstrations of
effectiveness strengthen causality arguments greatly. Since effects have
been found in a range of five national economic systems and in 47
previous research studies (M.U.M. 2004), these replications lend support
to a causal interpretation of the findings reported here. Many of the
previous studies use powerful time series analysis techniques, where
daily, weekly or monthly movements in the dependent variable above and
below the Maharishi Effect threshold have been shown to lead positive
and negative changes respectively in the dependent variables (see for
example Orme-Johnson et al. 1988). The prospective study of the
Maharishi Effect in Washington D.C. (Hagelin 1999) also bolsters the
argument for causality since the timing and size of the effect on
violent crime were predicted in advance.
Model sufficiency and fit: The rapid onset of
broad-based improvement in the IMD Index of social and economic
indicators and its subscales provides a very good fit with the phase
transition or step function model of Maharishi Effect theory used in
prior research (see Hatchard 2000 for a full discussion of theory).
Parameter constancy is also indicated since both New Zealand and Norway
had comparable effect sizes. Moreover the Cost Benefit Analysis and
previous research indicates USA, Norway, and New Zealand had similar
improvements in GDP, inflation, and unemployment, as did Cambodia and
Mozambique. All five nations enjoyed freedom from conflict and played a
peace role in world affairs when the Maharishi Effect threshold was
Alternative explanations: A crucial adjunct to
causal analysis must be a discussion of alternative explanations. For
example, OECD surveys seek to describe the causes of economic changes
among their member countries in terms of government policy, domestic
demand, strength of sectors, educational characteristics of the work
force, and international factors such as export demand, exchange rates,
and world economy. Particular emphasis is placed on the effect of
government policy. Therefore, in seeking to identify the causes of the
improvements in New Zealand, the OECD discussed the role of government
economic reforms that took place from 1983 to 1990. With hindsight, it
described the New Zealand economy as having "the least distorted
economy among OECD members".
Were the New Zealand fiscal reforms in the 1980's the cause of the 1993/4 improvements in IMD scores? In part, the answer is that the improvements were far broader than could be anticipated from the nature of the reforms. The improvements appeared in virtually all economic sectors. A close study of OECD Summaries shows that as late as December 1992, the OECD itself did not expect the sweeping economic reforms undertaken mainly in the mid 1980's to correct what it saw as fundamental imbalances in the New Zealand economy. In this, it was drawing upon its previous experience of the possible effects of government policy changes among its members.
Porter and Crocombe (Crocombe et al 1991, p. 8, 10, and 12) also reject this explanation strongly—"The failure of heavy government intervention was obvious, yet the early results of a rapid transition to a market economy appeared to hold little promise...Why despite one of the most rapid and far reaching economic liberalizations ever [begun eight years earlier], does our economy continue to languish and unemployment soar?...[This book] highlights how New Zealand's institutions and policies have retarded the progress of the economy."
Porter also suggested that the resource-dependent nature of the New
Zealand economy was indicative of poor prospects (Crocombe et al
1991). Moreover, other significant New Zealand economic commentators (Burnell
et al 1992) also believed as late as 1992 that not only was
there little prospect of a significant improvement in the economy, but
also that the government reforms of the 1980's had in fact harmed the
It is clear that the changes in government policy in New Zealand
occurred many years before the economic improvements from 1993 onwards.
Therefore it is natural for Porter and other economists to reject
government policy as an explanatory principle. Moreover, our analysis
and previous research has located parallel results in five nations, each
with radically different government policies.
Another possible explanation is the supposition that the economies of major trading partners improved sufficiently to stimulate the growth in New Zealand and Norway. However, our analysis is comparative and it demonstrates a larger improvement in New Zealand and Norway than their trading partners. Therefore this argument must be rejected.
In general the strongest argument against other explanations is the generalized nature of the IMD Index. It includes 224 social and economic factors. The simultaneously move of such a broad range of factors, strongly suggests an exogenous variable. The Maharishi Effect is the clear candidate for this position. Moreover, Cavanaugh (1987-89) controlled some other economic variables suggested by modern economic theory, and found that the influence of the Maharishi Effect on the Misery Index in USA was robust.
Effect of foreign investment: Foreign investment is
another alternative exogenous variable. By the end of 1994, both New
Zealand and Norway had dramatically increased their attractiveness to
foreign investors. On the IMD scale of attractiveness, New Zealand rose
from 9th overall to 5th and Norway from 23rd overall to 10th between
1993 and 1994. In 1994, there was a net inflow of overseas investment in
stocks of New Zealand companies of US$12.42 billion. This is US$3,500
for every man woman and child in New Zealand, the second highest level
of per capita overseas investment in the world (second only to
Singapore). This represents 22% of New Zealand's GDP, at the time the
fourth highest ratio of investment to GDP in the world (just behind
Singapore, Malaysia, and Indonesia). Norway has also had a large rise in
net inflow of overseas investment up from US$3.16 billion in 1992 to
US$14.33 billion in 1994. This shows the rapid growth in confidence that
the rest of the world had in the economies of New Zealand and Norway,
but the timing of the investment does not fit as a causal factor, since
foreign investment did not start to kick in until later in 1994 when the
massive shift in the economic prospects and performance had already
taken place and then began to attract international investors. The more
so since such investment was largely predatory of assets or land rather
than immediately stimulating new economic activity15.
Independent confirmation of economic progress: OECD Economic
Surveys: The improvements in the economies of New Zealand and
Norway have been independently assessed by OECD Surveys published
biannually. The surveys confirm the unusual, far reaching, unexpected,
and sustained nature of the economic resurgence in both countries. Among
other things, OECD surveys found that both New Zealand and Norway
enjoyed sustained periods of low inflation, high economic growth, and
low unemployment after the Maharishi Effect threshold was passed. It is
quite clear that the OECD was taken aback by the speed and depth of the
economic changes in both countries. The trends were not predicted
accurately in earlier forecasts and were characterized asatypical or
unexpected in later reports after the changes emerged in 1993/4.
Have the economic changes in Norway and New Zealand been
sustained?: The impact of the Maharishi Effect on the economy
of New Zealand and Norway has been modeled as a step function—in
1993/4 it is clear that the economy of both countries 'stepped up' to a
new level of performance. By the beginning of 1998, New Zealand and
Norway had enjoyed five years of sustained economic growth with low
inflation and low unemployment. The relevant 1999 OECD Economic Surveys
concluded that the
strong performance of the Norwegian economy since 1993 has lifted
mainland GDP by 20% in only five years, and during the last five years
New Zealand has experienced relatively rapid economic expansion by both
past and international standards.
Even so every economy remains subject to the influence of global
economic shocks and competitive trends. Both New Zealand and Norway are
small countries easily affected by the changing global economy. Both
rely on exports of primary products. Maharishi Effect theory suggests
that New Zealand and Norway should be more 'adaptable' in the face of
global economic shocks, but also that they will be vulnerable as long as
the other national economies to which they are linked through trade are
not using the Maharishi Effect themselves. Whilst the IMD Index has
enlarged in its data content sufficiently since 1998 to invalidate
statistical comparison with earlier years, OECD reports are indicative
of recent trends.
Recent trends in New Zealand: New Zealand's economy can be upset by changes in demand and prices for agricultural goods. It is also vulnerable to shifts in global climate. The 1999 OECD Survey discusses some of the obstacles that New Zealand has to overcome including the high and continuing trade barriers that New Zealand exporters face in markets for products in which it has a competitive advantage, and the country's relative geographic isolation and small size. Given these factors, the OECD concluded that the New Zealand economy had performed well. However, due to the Asian currency crisis, the economy slowed down in the first half of 1998, but the effect proved to be temporary. The 1999 OECD Survey reported that by the second half of 1998 a recovery was underway and was projected to gather strength in the near term with real GDP growth rising to around 3.5% in the year 2000. The June 2002 OECD survey summarized that the New Zealand economy had been remarkably resilient in the face of the mild world recession. With reference to defense, recently New Zealand has disbanded its strike air force, stayed out of the Iraq war, and played an successful peacekeeping role in the Pacific.
Recent trends in Norway: The 1999 Norway OECD Survey
commented on the sustained strong growth in Norway. It discussed soaring
oil and gas exports together with increasing sales of nonoil
'traditional' commodities, which contributed to a sharp widening of the
current account surplus.
Fixed capital formation was boosted by high profits and rising
capacity utilization, while substantial gains in real earnings buoyed
private consumption. Strong job creation raised the employment rate to
almost 80% of the working-age population (a record high), facilitated by
a flexible response from the labor force. At the same, time,
inflationary pressure remained subdued. The OECD also reported that by
1998 the potential for expanding the labor supply was almost exhausted
with record vacancies as the unemployment rate dropping below 3%. In
1998, the Norwegian economy was affected by oil price fluctuations and
by the government's own decision to limit oil production.
Later, in June 1999, the OECD Outlook attributed the mild 1998
economic slowdown directly to falls in oil prices; but there was a soft
landing for the Norwegian economy with mainland growth of 1% to 1.5% in
1999. Subsequently, high employment and large government surpluses have
continued to be buoyed by oil incomes. Since 2000, Norway has halved the
size of its military.
COST BENEFIT ANALYSIS
Other studies have assessed the economic impact of the Maharishi Effect through reduced crime (Hatchard 1996) and reduced healthcare costs (Herron 1996). These findings indicated substantial savings. Hatchard (2000 chap. nine) undertook a more global measure of the economic impact of the Maharishi Effect on the New Zealand economy whose conclusions we summarize here. Comparing 1988-92 and 1993-97 New Zealand had a relative increase in real GDP growth rate per capita of 3.28% p.a.. Excluding oil revenues, Norway had an increase in real GDP Growth rate of 3.43% p.a. after the Maharishi Effect threshold had been surpassed. To estimate of how much of the increase in GDP is due to the Maharishi Effect, Hatchard (2000) examined the principle sources of government revenue. New Zealand government treasury and OECD sources show that after the Maharishi Effect threshold was passed in 1993, the New Zealand government retired 23.5% of GDP in net total debt over a four-year period (figure 4). During this time real GDP increased from US$42.6 billion to US$47.5 billion.
Using OECD data, net debt was reduced from US$21.1 billion to US$12.4 billion. A total of US$8.7 billion in debt retirement. This is a very significant economic performance. The government had been facing a persistently high debt to GDP ratio that defied fiscally conservative reform prior to the Maharishi Effect threshold being passed in 1993, New Zealand's subsequent performance approximates the step function typical of the Maharishi Effect (Figure 4). The OECD Secretariat calculated that only one fifth of the debt reduction ($1.7 billion) could be accounted for by prior cyclical trends. This indicates a phase transition in the New Zealand economy when it reached the Maharishi Effect threshold in 1993 and supports our view reported elsewhere (Hatchard 2000) that the dynamics of the economy had changed.
The OECD also reported that during the 1994 -1997 period, the
government received NZ$3.24 billion (US$1.62 billion) in sales of assets
and lowered personal income tax rates by 0.6% of household income and
indirect taxes by 0.5% of GDP during this four-year period—a total of
approximately US$1.36 billion. Taking the headline figure of US$8.7
billion in net government debt reduction, subtracting the US$1.96
billion identified as resulting from previous trends and the US$1.62
billion in asset sales, and adding the US$1.36 in tax reductions, the
New Zealand government had a net gain of US$6.48 billion over four
During this four-year period, economic activity increased by US$14.44
billion compared to the previous trend. This yielded a tax revenue
benefit @ 38% of US$5.49 billion to the New Zealand Government. In
addition, the government benefited by US$1.02 billion in reduced welfare
payments to the unemployed. The sum of increased tax revenues and
reduced unemployment benefits is US$6.51 billion.
The cost of instructing one per cent of the population of New Zealand
in the Transcendental Meditation program at 1999 prices is 38,000 x $575
= NZ$21.85 million (US$10.93 million).
In summary the New Zealand Government had a net debt reduction of
US$6.48 billion, which, according to the OECD, could not be accounted
for by previous cyclical trends and a net increase in revenues from
increased tax-take and reduced unemployment of US$6.51 billion. The
equivalence of these two headline figures suggests that the net increase
in tax revenues was the entirely the result of new economic factors not
predicted by previous economic trends. On this basis, it would be very
conservative to rely on Cavanaugh's time series analysis (1987-89),
which reports that 54% of the reduction in the Misery Index in the USA
was due to the Maharishi Effect. Taking 54% of the improved economic
performance of New Zealand to be the result of the Maharishi Effect, we
arrive at $713 increase in GDP over four years for each $1 spent
implementing the Maharishi Effect and corresponding benefits to the
government coming to $320. This suggests that each person learning the
Transcendental Meditation program generated US$205,000 in increased GDP
over a four-year period.
The Maharishi Effect as an economic multiplier: Our
cost-benefit summary suggests that the Maharishi Effect can added to any
economic system as an economic multiplier. In effect a cascade of
benefits are stimulated in the economy; the estimated government saving
of $320 for every dollar invested represents an annual rate of return on
capital of 8,000%. Moreover, some savings are unquantified due to either
a lack of empirical data to support an estimate or the essentially
'priceless' and vital nature of commodities such as 'stable peace',
'good health', 'improved education', or 'creativity and innovation'.
The empirical data and statistical analysis presented in this study
lends support to the hypothesis that the Maharishi Effect had a
substantial impact on the IMD Index scores of National Competitive
Advantage for both New Zealand and Norway. This suggests a basis for
wealth generation in an integrated approach to national economic
development. Results of analysis, previous research and case studies
reported here appear to provide governments with a simple-to-implement,
highly costeffective intervention to develop national human resources,
multiply investment, and improve economic performance.
We have found that as the Maharishi Effect stimulates economic
growth, the wealth generated is distributed in different ways through
the economic channels that are active in that nation, and by the
government via the taxation and spending process. In New Zealand and
Mozambique debt repayment was a priority for their governments. This was
achieved on a massive and unprecedented scale after the Maharishi Effect
threshold was passed. Currently the New Zealand government is cushioned
by a massive current account and asset surplus, rare in the modern
world. In Norway, the government has spent heavily on social welfare,
health, and education. In the USA, lower tax rates were a political
priority. In Cambodia, economic, educational, and infrastructure
projects have regenerated the economy of the nation.
In summary, we have found evidence that the Maharishi Effect is applicable to a variety of economies, small and large, poor and rich, agricultural and industrial. Once the participation threshold is passed, the effect leads to broad-based improvements affecting diverse sectors of the economy and measures of quality of life. Our analysis is also consonant with previous research on the Maharishi Effect, which shows reduced crime, violence, and conflict and enhanced progress towards peace. As such, it represents a unique form of ethical investment that appears to not only create the peaceful and orderly conditions necessary to underpin economic growth but also to dynamically multiply itself hundreds of times in the wider economy thereby benefiting the entire population by stimulating GDP, as well as reducing unemployment, inflation, and government debt. This understanding extends the growing perception that human factors underly the growth and stability of economic systems (Romer 1996). Dr. Huw Dixon, Professor of Economics at the University of York and Associate Editor of the Economic Journal has suggested that government policy should be guided by the results of research on the Maharishi Effect (1996):
The universities will each house coherence creating groups of 1-200
Yogic Flyers and offer Consciousness-Based Educational programs for the
population at large. Maharishi's proposal includes the creation of a
number of groups of 8000 Yogic Flyers—one in USA and several in India.
Maharishi refers to this program as a 'Peace Government', which he
predicts will quietly improve the global economy and generate more
peaceful world events (MOU 2004).
We conclude that the maintenance of tolerance and peace, the happy, harmonious coexistence of peoples and beliefs, and the economic vitality of nations all rely on the well being of the individual and social mind. In essence, our findings suggest that the secret of nationhood and good government lies in the development of the alertness, creativity, and consciousness of individual citizens. This understanding is rooted in the Vedic tradition, which Maharishi represents. His unique contribution lies in the rediscovery that only a few individuals practicing Vedic technologies to develop full consciousness is a powerful means to maintain the peace and well being of nations.
Guy D. Hatchard Ph.D.
Guy Hatchard Ph.D.
Dr. Hatchard's research interests combine diverse academic and practical themes including research on crime prevention, health care delivery, education, economic development, conflict resolution, and food safety. The central thesis of his published research work is that Transcendental Meditation is a method to reduce stress and enhance educational and health outcomes which has a highly significant impact on programs to resolve crime and conflict and ensure economic stability. He has helped to pioneer research programs using field-based models from the physical sciences to analyse social and economic indicator data series.
Research on Social Indicators
Since 1976, Dr. Hatchard has conducted research and supervised projects to implement prevention-orientated health care systems and crime prevention programs utilising the Transcendental Meditation program in UK, USA, and New Zealand. This has particularly included the use of time series intervention analysis and panel regression analysis to model crime rates and show how they can be reduced and economic development stimulated by using the Transcendental Meditation program to reduce the overall levels of stress and enhance the creative potential of society.
In 2000, Dr. Hatchard completed his Ph.D. thesis investigating the relation between the development of creative potential and the economic, innovative, competitive, and social performance of New Zealand, Norway, USA, Mozambique, Metropolitan Merseyside, UK, and Wellington, NZ in relation to other 46 industrialised economies. He used data on participation rates in the popular means of developing creative potential—Transcendental Meditation—to analyse the relationship between innovation and broad-based measures of economic and social health using time series and regression analysis of panel data involving the analysis of 224 social statistics for each of 46 countries. Drawing on the theoretical framework of Michael Porter and others, he has demonstrated a strong relationship between the development of the human resources of creativity, innovation, and entrepreneurial skill and the development of national economic potential. His research shows how stress-reducing methods can be a crucial element in programmes to improve educational and health outcomes and thereby impact successfully on the transition from conflict to peace.
He has undertaken research in secondary level curriculum design for mastery learning, equal opportunity learning and evaluation regimes, and personal development of academic and creative potential. Dr. Hatchard has developed an overall learning strategy incorporating six approaches which enhanced achievement and enjoyment of learning:
Food Safety, Health, Regulatory, and Trade Systems
In the light of recent concerns about global food safety and biointegrity, Dr. Hatchard has worked on an internet-based, point-to-point system of safe food trading backed up by genetic and conventional testing schemes. He is also currently working on a four dimensional taxonomy of medical intervention effectiveness.
Career Achievements and Highlights:
Guy Hatchard has not only undertaken ground-breaking research on the Maharishi Effect, (the phenomenon whereby a few individuals practising the Transcendental Meditation program and Yogic Flying in a group can reduce negative trends such as crime and violence and enhance positive trends including economic development, national well being and world peace), but he has also applied his research findings to develop practical programmes for the good of society.
From 1990 to 1996 he was Director of MESA, a non-profit community development trust within Skelmersdale new town UK with a total capitalisation over £20 (NZ$50) million which comprises over 300 members, a natural health care clinic, an award-winning school, a community centre, a recreation centre, 60 houses, and a business incubation centre. Under Dr. Hatchard's direction, MESA organised a crime prevention program in Merseyside, which has helped to reduce crime by 60% relative to other metropolitan areas. This finding was published in 1996 in Vol 2:3 of Psychology, Crime, and Law. In 1993, Dr. Hatchard was honoured as a key note speaker at the Annual Conference of the British Psychological Society on Criminal and Legal Psychology. In 1999, the MESA project won the prestigious BUPA (British Urban Renewal Association) award for best practice.
From 1996 - 2000 he was the founding Director of the Natural Food Commission. In this role, Dr. Hatchard travelled widely and lectured throughout the Pacific region and Europe. In 2000, he testified before the Royal Commission on Genetic Modification. In 1998, he was invited to address MPs from all parties at the Parliament House. In 1997, he was keynote speaker at the Annual Conference of PANAPS in Malaysia. In 1997, he gave a series of lectures in Australia and met with State Ministers of Health. In 1997, Dr. Hatchard was nominated to the NZ Minister of Consumer Affairs by Greenpeace, the Wellington Safe Food Campaign, and the Pacific Institute of Resource Management as a NZ consumer representative on the Australia New Zealand Food Authority.
In 1990, he was director of a 20 person Maharishi Foundation medical relief team in Armenia after the catastrophic 1989 earthquake in which programme over 35,000 Armenians participated.
Currently Dr. Hatchard is planning an Institute for Health, Education and Well Being in Wanaka, New Zealand.
Kenneth Cavanaugh, Ph.D.
Kenneth Cavanaugh, Ph.D.
Dr. Ken Cavanaugh received his undergraduate degree with honors from Yale University (1964), Master's degrees from Princeton University (1969) and Stanford University (1973), Ph.D. from the University of Washington (1983), and Doctorate in World Peace (DWP) from Maharishi European Research University (2005).
Dr. Cavanaugh's research has primarily focused on empirical
investigation of potential impacts of field effects of consciousness on
the quality of life in society. He has authored or co-authored more than
30 published papers on social-indicators research and as well as other
topics in applied statistics.
His research has been published in many leading journals, including Social Indicators Research, Journal of Social Behavior and Personality, Proceedings of the American Statistical Association, The Journal of Mind and Behavior, Journal of Offender Rehabilitation, Journal of International Money and Finance, Cancer Research, Modern Science and Vedic Science, and Psychology Crime and Law. Many of these publications on social-indicators research have been reprinted in several volumes of Scientific Research on Maharishi's Transcendental Meditation and TM-Sidhi Programme: Collected Papers.
Career Achievements and Highlights:
A consistent theme running through Dr. Cavanaugh's career is his interest in education as well as in efforts to promote world peace and an improved quality of life in society. While on leave from graduate studies at Princeton University, Dr. Cavanaugh worked from 1966 to 1968 in the field of peace education with the World Without War Council of Greater Seattle, a non-profit educational organization that promotes peaceful solutions to violent conflict.
After receiving his Master's degree in Public and International Affairs from the Woodrow Wilson School of Public and International Affairs at Princeton in 1969, Dr. Cavanaugh served as Regional Director of Admissions at Princeton University. He was responsible for international admissions as well as for admissions activities in 27 states in the U.S.
From 1973 to 1975, Dr. Cavanaugh served as Special Assistant to the President, University Secretary, and Dean of International Affairs at Maharishi International University (now Maharishi University of Management). After completing his Master's degree at Stanford University in 1973 he was inspired to join the faculty at MIU because of its innovative consciousness-based approach to higher education. Through this approach, MUM seeks to develop the full creative potential of the student by promoting integrated brain functioning and simultaneously providing high-quality training in traditional academic disciplines. The University's commitment to promoting world peace and an improved quality of life in society through scientifically validated, consciousness-based technologies was also a major attraction.
While on leave from MUM, Dr. Cavanaugh completed his doctoral training at the University of Washington in Seattle. After receiving his Ph.D. in 1983 he rejoined the faculty of MUM in the School of Business and Public Administration, helping to found its new Master of Business Administration and Ph.D. programs. From 1991 to 1993 he served as Director of the School's undergraduate program in Government and Public Policy and taught courses in peace studies and international relations in that program.
In 1990, Dr. Cavanaugh was director of an 8-person team of scientists and other faculty from Maharishi University of Management that lectured and taught for seven months in Russia and Ukraine at leading scientific institutes, medical research institutes, medical clinics, universities, government ministries, and as well as other public venues. The team presented scientific research on consciousness-based solutions to challenges facing those countries in the areas of individual and public health, societal conflict and crime, economic prosperity, and world peace.
In 1993, Dr. Cavanaugh taught at Maharishi Institute of Management in Kenya. From 1995 to 1997, Dr. Cavanaugh served as the founding President of MUM's proposed branch campus in Chicago, Maharishi University of Management in Chicago.
In addition to conducting research on the field effects of consciousness and the quality of life, Dr. Cavanaugh currently guides doctoral students in their dissertation research and teaches graduate courses in statistical analysis and research methods in the Department of Business Administration at MUM. In addition to his faculty duties at MUM, Dr. Cavanaugh currently serves as President of Invincibility Foundation, Fairfield, Iowa (2008 to present). The foundation supports innovative, scientifically validated, consciousness-based approaches to promoting world peace and an improved quality of life in society.
1. © 1999 Maharishi University of Management. ® Transcendental
Meditation, TM-Sidhi, TM, Consciousness-Based, Maharishi, Maharishi
Vedic Approach to Health, Maharishi University of Management, and
Maharishi VedicScience are registered or common law trademarks licensed
to Maharishi Education Development Corporation and used under sublicense
or with permission.
2. Cambodia and Mozambique both had long standing civil conflicts
before adopting Maharishi's programs. Namibia was engaged in a war of
independence against the white South African regime. The implementation
of Consciousness-Based Education programs in the black townships and
cities of South Africa and its influence on national development is not
covered in this paper. Editor's Note: More information about
about Invincible Defense Technology in South Africa see: http://www.InvincibleSouthAfrica.org
3. These eight categories are defined as: Domestic Economy—macroeconomic
evaluation of the domestic economy, Internationalization—participation
in international trade and investment flows, Government—extent
to which government policies are conducive to competition, Finance—performance
of capital markets and quality of financial services, Management—enterprise
management in an innovative, profitable, and responsible manner, Infrastructure—extent
to which resources & systems are adequate to meet the needs of
business, Science and Technology—capacity and success
of basic and applied research, People—availability
and qualifications of human resources
4. Beck and Katz (1995) suggest that the fixed-effects model (FEM) is
more appropriate for cross-country studies than a random-effects model
(REM) or error-components model. The FEM model is appropriate because
the objective is to draw statistical inferences that are confined to the
OECD countries in the sample, a sample that was not randomly selected (Hsiao,
1986, p. 43; Baltagi, 1995, p. 10). Using an REM model, the estimate of
the Maharishi Effect parameter β1 was very close, both in
magnitude and statistical significance, to the corresponding FEM
estimate in Table 2.
5. In matrix notation, the fixed-effect model of equation (1) may be
written as follows:
y = X β + ε .
In this equation, y is an N x 1 column vector of
values of the dependent variable, IMDit, for each of the 46
countries. In the primary analysis of the current study T = 7, G
= 46, and the total sample size is N = TG = 322. For
all vectors and matrices in this equation, the values of the T
longitudinal values for each different country are stacked on top of
each other in sequential (time) order by country. The N x (G
+ 1) matrix X of explanatory variables
contains G columns of dummy binary variables, one for each
country, plus one column of observations on the independent variable,
the Maharishi Effect dummy variable MEit. The matrix β
is a (G + 1) x (G + 1) matrix of regression
coefficients. The error matrix ε is a N
x 1 vector of random disturbances, with error covariance matrix Ω
having typical element E(εit εjt) and dimension N
6. More formally, the OLS estimates of the regression slope
coefficients in (1) will be optimal in the sense defined here if the
errors eit are independent and identically distributed with mean zero
and variance σ 2 with covariance matrix Ω =
σ 2 I, where I is a T x T
identity matrix. It is also required that the explanatory variables X
be independent of the errors, εit, for all i and t.
Balestra (1996) discusses further assumptions required to establish the
consistency of OLS estimates of the intercept terms in the FEM. The
consistency of the estimated intercepts in the fixed-effects model
requires the assumption that the total sample size N increases by
holding G fixed while T is increased to infinity. The regression slope
coefficients are consistent no matter how N is increased.
7. The calculation of the panel-corrected standard errors may be described as follows (Beck and Katz, 1996). If the regression residuals are arranged in a T x G matrix E, with the G columns of E made up of T residuals for each country, then a consistent estimate of the G x G matrix of error variances and contemporaneous covariances is given by
Σ = (E' E)/ T
with σi 2 along the matrix diagonal and σij off the diagonal. Since the errors are assumed to be serially independent, the estimated variance-covariance matrix of the errors is given by
Ω = Σ ⊗ IT
where ⊗ denotes the Kronecker product and IT
is a T x T identity matrix. The PCSEs are estimated by
the square root of the diagonal elements of the k x k
matrix resulting from the following matrix operations
(X'X)−1 X' Ω
where X is the N x k matrix of independent
8. For the sample analyzed in the current study, the elements of the
contemporaneous correlation matrix for the residuals are very
imprecisely estimated. Each of the G x (G + 1)/2
contemporaneous correlations in the G x G correlation
matrix for the errors ε are estimated using, on average, 2T/G
observations (Beck and Katz, 1995). For the current study T
(the number of time series observations for each country, 7) is less
than G (the number of countries, 46). Thus, less than one
observation is available to estimate each element of the error
9. The RESET test was designed to test for omitted explanatory
variables but it is also a powerful test for incorrect functional form,
such as non-linearities (Kennedy, 1998, p. 98, 80). The variant of the
test employed here was based on auxiliary OLS regression in which the
predicted (fitted) values from the OLS regression raised to the power
two, three, and four were added to the original regression equation to
proxy for the effects of possible unknown omitted explanatory variables
(Godfrey, 1988, ch. 4). The RESET test is an F-test for the
joint statistical significance of these three additional variables.
10. This higher score is commensurate with scores from the World
Economic Forum Index of international competitiveness, which placed New
Zealand 3rd and Norway 7th in 1996. The World Economic Forum Index used
to work jointly with IMD, but since 1996 it has published its own Index,
which places more emphasis than IMD on openness to trade and investment,
the efficiency of government and the financial sector, labor market
flexibility and educational attainment.
11. Due to a near-singular matrix it was not possible to calculate
the RESET test for the regression reported in Table 3.
12. The same feasible generalized least squares (FGLS) procedure used
in the primary analysis was employed to correct for first-order serial
correlation of the regression residuals. To conserve space, these
adjusted regression results are not shown here but they are available
upon request from the authors.
13. Volatility in the IMD overall scores results partly from the
survey content of the Index (33%). Surveys reflect both the long and
short term views of participating executives, they also reflect changes
in national mood. This can mirror the current business and political
climate, which can be subject to short term fluctuations. The IMD Index
is also sensitive to regional economic factors, currency fluctuations,
overseas investor confidence, stability of specific global markets, and
14. Economic theory predicts that there should be a negative
relationship between unemployment rate and economic growth. This
empirical regularity known as 'Okun's Law' states that the unemployment
rate will decline by 0.4% for every 1% of annual real GNP growth above
its trend rate of growth (Dornbusch et al 1988). This was not
the case during the recovery in Finland, which underlines the unusual
nature of the economic changes taking place there.
15. Many major domestic companies such as the New Zealand Telecom
company have become wholly or partly owned by overseas interests. the
result is that many decisions that used to be made in the coherent
atmosphere of either New Zealand or Norway, which both enjoyed the
benefits of the Maharishi Effect, are now made increasingly in overseas
countries, where the collective consciousness is not so harmonious and
wholly supportive of their interests. For example, the 1999 OECD Survey
of Norway concluded that even though GDP growth was still running at
2.5% to 3%, investor concerns triggered substantial capital outflows
after the summer of 1998. The exchange rate plunged, interest rate
soared, and the current account surplus, which had reached a record of
6% in the previous two years, vanished in 1998. In a sense, foreign
investment is especially predatory. Foreign investors are looking for
monetary gains; they do not necessarily care about the long term
interests of target countries. They will tend to pull the plug on
investments for short-term reasons (Naylor 1994, Patnaik 1997). In
Norway's case, a natural slowdown in growth rates, as capacity limits
and full employment were reached, was turned, by panicky investors, into
a major fluctuation in the domestic economy, which tended to undermine
consumer confidence and business profits.
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